Spark submit does automatically upload the jar to cluster? - apache-spark

Question

I'm trying to submit a Spark app from local machine Terminal to my Cluster.
I'm using --master yarn-cluster. I need to run the driver program on my Cluster too, not on the machine I do submit the application i.e my local machine
When I provide the path to application jar which is in my local machine, would spark-submit automatically upload it to my Cluster?
I'm using
bin/spark-submit
--class com.my.application.XApp
--master yarn-cluster --executor-memory 100m
--num-executors 50 /Users/nish1013/proj1/target/x-service-1.0.0-201512141101-assembly.jar
1000
and getting error
Diagnostics: java.io.FileNotFoundException: File file:/Users/nish1013/proj1/target/x-service-1.0.0-201512141101- does not exist
In Documentation ,http://spark.apache.org/docs/latest/submitting-applications.html#launching-applications-with-spark-submit
Advanced Dependency Management When using spark-submit, the
application jar along with any jars included with the --jars option
will be automatically transferred to the cluster.
But seems like it does not !

Answer 1

I see you are quoting the spark-submit page from Spark Docs but I would spend a lot more time on the Running Spark on YARN page. Bottom-line, look at:
There are two deploy modes that can be used to launch Spark
applications on YARN. In yarn-cluster mode, the Spark driver runs
inside an application master process which is managed by YARN on the
cluster, and the client can go away after initiating the application.
In yarn-client mode, the driver runs in the client process, and the
application master is only used for requesting resources from YARN.
Further you note, "I need to run the driver program on my Cluster too, not on the machine I do submit the application i.e my local machine"
So I agree with you that you are right to run --master yarn-cluster instead of --master yarn-client
(and one comment notes what might just be a syntax error where you dropped "assembly.jar" but I think this will apply as well...)
Some of the basic assumptions about non-YARN implementations change a lot when YARN is introduced, mostly related to Classpaths and the need to push jars to the workers.
From an email on the Apache Spark User list:
YARN cluster mode. Spark submit does upload your jars to the cluster.
In particular, it puts the jars in HDFS so your driver can just read
from there. As in other deployments, the executors pull the jars from
the driver.
So finally, from the Apache Spark YARN doc:
Ensure that HADOOP_CONF_DIR or YARN_CONF_DIR points to the directory
which contains the (client side) configuration files for the Hadoop
cluster. These configs are used to write to HDFS and connect to the
YARN ResourceManager.
NOTE: I only see you adding a single JAR, if there's a need to add other JARs there's a special note about doing that with YARN:
In yarn-cluster mode, the driver runs on a different machine than the
client, so SparkContext.addJar won’t work out of the box with files
that are local to the client. To make files on the client available to
SparkContext.addJar, include them with the --jars option in the launch
command.
That page in the link has some examples.
And of course you downloaded or built the YARN-specific version of Spark.
Background, in a standalone cluster deployment using spark-submit and the option --deploy-mode cluster, yes you do need to make sure every worker node has access to all the dependencies, Spark will not push them to the cluster. This is because in "standalone cluster" mode with Spark as the job manager, you don't know which node the driver will run on! But that doesn't apply to your case.
But if I could, depending on the size of the jars you are uploading, I would still explicitly put the jars on each node, or "globally available" via HDFS, for another reason from the docs:
From Advanced Dependency Management, it seems to present the best of both worlds, but also a great reason for manually pushing your jars out to all nodes:
local: - a URI starting with local:/ is expected to exist as a local
file on each worker node. This means that no network IO will be
incurred, and works well for large files/JARs that are pushed to each
worker, or shared via NFS, GlusterFS, etc.
But I assume that local:/... would change to hdfs:/ ... not sure on that one.

Answer 2

Yes and no. It depends on what you mean. Spark deploys the .jar to the nodes in the cluster. However, it won't upload your .jar file from your local machine to the cluster.
You can find more info in the Submitting Applications page. As you can see, in the arguments you pass to spark-submit, there is one that needs to be globally visible: the application-jar.
application-jar: Path to a bundled jar including your application and
all dependencies. The URL must be globally visible inside of your
cluster, for instance, an hdfs:// path or a file:// path that is
present on all nodes.
As far as I understand, what you want is to use yarn-client, not yarn-cluster. This will run the driver in the client (e.g., the machine which you are trying to call spark-submit on, for example your laptop), without the need of copying the .jar file on the cluster. More about this here.

Answer 3

Try adding --jars option before your /path/to/jar/file
spark-submit --jars /tmp/test.jar